The present disclosure discloses a method and apparatus for changing a resource state, a terminal, and a storage medium, which belong to the field of smart home. A system for changing a resource state that includes a first collection resource, a first intermediate-level resource, and leaf node resources can be established. By making the first collection resource obtain link information of each leaf node resource whose resource state needs to be changed, a request that includes a default interface of the leaf node resource may be generated for the leaf node resource, such that a state of the leaf node resource can be changed accurately by the system. Therefore, the present disclosure enables the control request issued by a client to be recognized and executed by each leaf node resource, thereby increasing reliability and stability of system control.

When it is determined that a position of the display terminal is within a range of a prescribed distance from the house and when it is determined that the log information and the information indicating the operational state of the one electric home appliance are not consistent with each other, the server provides the display terminal with information on a possibility of a malfunction of the one electric home appliance while the position of the display terminal is still within the range of the prescribed distance from the house.

Improved systems, methods, and architectures to enhance decision making in Smart Cities and Smart Regions. A system includes an index structure including a first hierarchical data structure including a first hierarchical score based on a plurality of first-level elements, each of the plurality of first-level elements having a respective weighting, and a second hierarchical data structure including a plurality of second hierarchical scores based on a plurality of second-level elements, each of the plurality of second-level elements having a respective weighting, such that the first hierarchical score is based on the plurality of second hierarchical scores through an index factor; and a computer-implemented regional monitor engine to manage local access to a plurality of external data sources to coordinate writes to the index structure.

Improved systems, methods, and architectures to enhance decision making in Smart Cities and Smart Regions. A system includes an index structure including a first hierarchical data structure including a first hierarchical score based on a plurality of first-level elements, each of the plurality of first-level elements having a respective weighting, and a second hierarchical data structure including a plurality of second hierarchical scores based on a plurality of second-level elements, each of the plurality of second-level elements having a respective weighting, such that the first hierarchical score is based on the plurality of second hierarchical scores through an index factor; and a computer-implemented regional monitor engine to manage local access to a plurality of external data sources to coordinate writes to the index structure.

A network of motion sensors employs sensitive accelerometers to issue time-domain measurements of building movement from multiple locations within and between buildings and other structures. The time-domain measurements from the various motion sensors are synchronized and converted into frequency-domain measurements of building movement. Individual motion sensors can be equipped with the requisite processor and memory to synchronize and covert the time-domain measurements. The motions sensors can classify detected events into various event types, such as earthquakes, wind events, or bipedal locomotion. The sensors can also communicate with one another or other resources to calculate event probabilities. A motion sensor may, for example, receive an earthquake-verification signal responsive to an earthquake-verification request. The network of motion sensors can calculate local soil stiffness and financial loss estimations responsive to their individual or collective frequency-domain measurements.

An Internet of things (IoT) wireless communication module. The IoT wireless communication module comprises an antenna, a radio transceiver coupled to the antenna, an embedded universal integrated circuit card (eUICC) coupled to the radio transceiver, where the eUICC is provisioned with a plurality of eSIM profiles, a non-transitory memory, a processor coupled to the non-transitory memory, to the radio transceiver, and to the eUICC, and an eSIM profile adapter application stored in the non-transitory memory. When executed by the processor, the eSIM profile adapter application determines a system installation context of the IoT wireless communication module, selects one of the plurality of eSIM profiles stored in the eUICC based on the system installation context, and activates the selected eSIM profile in the eUICC.

Embodiments for ensuring compliance of Internet of Things (IoT) devices in an IoT environment by a processor. One or more solutions may be provided for those of a plurality of sensor based devices in an IoT network identified as having performance obligation deficiencies according to a knowledge domain describes the performance obligations for the plurality of sensor based devices.

Embodiments for ensuring compliance of Internet of Things (IoT) devices in an IoT environment by a processor. One or more solutions may be provided for those of a plurality of sensor based devices in an IoT network identified as having performance obligation deficiencies according to a knowledge domain describes the performance obligations for the plurality of sensor based devices.

The present disclosure advantageously provides devices, systems, and methods for facility analytics. A computer-based method for determining electrical energy consumption for a building includes receiving static data for a plurality of electrical energy-consuming equipment (EECE) associated with the building, receiving dynamic data for each EECE, determining an electrical energy consumption value for each EECE over a predetermined time period, and determining a building electrical energy consumption value over the predetermined time period. The static data includes one or more performance attributes for each EECE, and the dynamic data includes measured performance data for each EECE over the predetermined time period. The electrical energy consumption value for each EECE is determined based on the performance attributes for each EECE and the measured performance data for each EECE. The building electrical energy consumption value is determined based on the electrical energy consumption value for each EECE.

The present disclosure advantageously provides devices, systems, and methods for facility analytics. A computer-based method for determining electrical energy consumption for a building includes receiving static data for a plurality of electrical energy-consuming equipment (EECE) associated with the building, receiving dynamic data for each EECE, determining an electrical energy consumption value for each EECE over a predetermined time period, and determining a building electrical energy consumption value over the predetermined time period. The static data includes one or more performance attributes for each EECE, and the dynamic data includes measured performance data for each EECE over the predetermined time period. The electrical energy consumption value for each EECE is determined based on the performance attributes for each EECE and the measured performance data for each EECE. The building electrical energy consumption value is determined based on the electrical energy consumption value for each EECE.